# How to integrate Backendless MCP with Vercel AI SDK v6 ```json { "title": "How to integrate Backendless MCP with Vercel AI SDK v6", "toolkit": "Backendless", "toolkit_slug": "backendless", "framework": "Vercel AI SDK", "framework_slug": "ai-sdk", "url": "https://composio.dev/toolkits/backendless/framework/ai-sdk", "markdown_url": "https://composio.dev/toolkits/backendless/framework/ai-sdk.md", "updated_at": "2026-05-12T10:02:19.950Z" } ``` ## Introduction This guide walks you through connecting Backendless to Vercel AI SDK v6 using the Composio tool router. By the end, you'll have a working Backendless agent that can list all files in the user uploads folder, create a new directory for project assets, retrieve users where status is active through natural language commands. This guide will help you understand how to give your Vercel AI SDK agent real control over a Backendless account through Composio's Backendless MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate Backendless with - [OpenAI Agents SDK](https://composio.dev/toolkits/backendless/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/backendless/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/backendless/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/backendless/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/backendless/framework/codex) - [OpenClaw](https://composio.dev/toolkits/backendless/framework/openclaw) - [Hermes](https://composio.dev/toolkits/backendless/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/backendless/framework/cli) - [Google ADK](https://composio.dev/toolkits/backendless/framework/google-adk) - [LangChain](https://composio.dev/toolkits/backendless/framework/langchain) - [Mastra AI](https://composio.dev/toolkits/backendless/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/backendless/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/backendless/framework/crew-ai) ## TL;DR Here's what you'll learn: - How to set up and configure a Vercel AI SDK agent with Backendless integration - Using Composio's Tool Router to dynamically load and access Backendless tools - Creating an MCP client connection using HTTP transport - Building an interactive CLI chat interface with conversation history management - Handling tool calls and results within the Vercel AI SDK framework ## What is Vercel AI SDK? The Vercel AI SDK is a TypeScript library for building AI-powered applications. It provides tools for creating agents that can use external services and maintain conversation state. Key features include: - streamText: Core function for streaming responses with real-time tool support - MCP Client: Built-in support for Model Context Protocol via @ai-sdk/mcp - Step Counting: Control multi-step tool execution with stopWhen: stepCountIs() - OpenAI Provider: Native integration with OpenAI models ## What is the Backendless MCP server, and what's possible with it? The Backendless MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Backendless account. It provides structured and secure access to your backend services, so your agent can perform actions like managing file storage, retrieving and updating database records, handling directories, and orchestrating server-side logic on your behalf. - Dynamic file and directory management: Allow your agent to create, copy, delete, and list files or folders in your Backendless storage, keeping your app data organized. - Database record retrieval and filtering: Empower the agent to fetch objects from specific tables with advanced filtering, sorting, and pagination for instant data access. - Automated backend task scheduling: Let the agent create or delete timers to run recurring or one-off server-side logic, enabling powerful backend automation. - Custom Hive resource management: Instruct your agent to create new Backendless Hive resources and retrieve full maps of stored values for scalable, flexible data handling. - Safe data cleanup: Make it easy for your agent to remove obsolete files, directories, or scheduled tasks, helping maintain a tidy and efficient backend environment. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `BACKENDLESS_COPY_FILE` | Copy File | Tool to copy a file or directory within Backendless file storage. Use when duplicating files to a new location after verifying source and destination paths. | | `BACKENDLESS_CREATE_DIRECTORY` | Create Directory | Tool to create a new directory at the specified path. Use when you need to organize files under a new folder structure. | | `BACKENDLESS_CREATE_HIVE` | Create Backendless Hive | Tool to create a new Hive. Use when you need to provision a new Hive resource before performing Hive operations. Example: Create a hive named 'groceryStore'. | | `BACKENDLESS_CREATE_TIMER` | Create Backendless Timer | Tool to create a new timer with schedule and code. Use when scheduling recurring or one-off tasks to run server-side logic after confirming parameters. | | `BACKENDLESS_DELETE_DIRECTORY` | Delete Directory | Tool to delete a directory at the specified path in Backendless file storage. Use when you need to remove folders after confirming the path. | | `BACKENDLESS_DELETE_FILE` | Delete File | Deletes a file from Backendless file storage at the specified path. Use this tool when you need to remove files from storage. The operation is permanent and cannot be undone. Ensure the file path is correct before deletion. | | `BACKENDLESS_DELETE_TIMER` | Delete Backendless Timer | Deletes a Backendless timer by its unique name. Use this tool to permanently remove a scheduled timer from your Backendless application. The timer must exist and you must provide its exact name. Once deleted, the timer's scheduled executions will stop immediately and cannot be recovered. Note: Requires access to Backendless Console Management API (available with Plus or Enterprise plans). | | `BACKENDLESS_DIRECTORY_LISTING` | Directory Listing | Tool to retrieve a listing of files and directories at a given path. Use when browsing or filtering file storage directories. | | `BACKENDLESS_GENERAL_OBJECT_RETRIEVAL` | General Object Retrieval | Tool to retrieve objects from a specified Backendless table with filtering, sorting, and pagination. Use after confirming the table name and query options. Example: "Get Users where age > 30 sorted by created desc". | | `BACKENDLESS_GET_ALL_VALUES` | Get All Values | Tool to retrieve all values from a map in a specified Hive. Use when you need to fetch the entire contents of a Hive map at once. | | `BACKENDLESS_GET_COUNTER_VALUE` | Get Counter Value | Tool to retrieve the current value of a Backendless counter. Use when you need to inspect an atomic counter's value. | | `BACKENDLESS_GET_FILE_COUNT` | Get File Count | Tool to get the count of files in a Backendless directory. Use when you need to determine how many items match a filter or include subdirectories. | | `BACKENDLESS_GET_KEY_ITEMS` | Get Key Items | Tool to retrieve values for a specified key in a list (all, single, or range). Use when you need specific elements or the entire list from a Hive key. Supports single index retrieval, range retrieval, or full list. | | `BACKENDLESS_GET_TIMER` | Get Backendless Timer | Tool to retrieve information about a specific timer. Use when you need to inspect a timer's schedule and next run details by name. | | `BACKENDLESS_MAP_PUT` | Map Put | Tool to set or update key-value pairs in a Hive map. Use when you need to add or update multiple entries in a Hive map. | | `BACKENDLESS_MOVE_FILE` | Move File | Tool to move a file or directory within Backendless file storage. Use when relocating resources to a new path after verifying source and destination. | | `BACKENDLESS_PUBLISH_MESSAGE` | Publish Message | Tool to publish a message to a specified messaging channel. Use when you need to send notifications or events to subscribers after confirming channel and payload. | | `BACKENDLESS_RESET_COUNTER` | Reset Counter | Tool to reset a Backendless counter back to zero. Use when you need to reinitialize a counter before starting a new sequence. | | `BACKENDLESS_SET_COUNTER_VALUE` | Set Counter Value | Tool to set a Backendless counter to a specific value conditionally. Use when you need to ensure the counter only updates if it currently matches an expected value. | | `BACKENDLESS_UPDATE_TIMER` | Update Backendless Timer | Tool to update schedule or code of an existing timer. Use when you need to modify a timer's configuration after retrieval. | | `BACKENDLESS_USER_DELETE` | Delete User | Tool to delete a user by user ID. Use when removing a user account after confirming permissions. | | `BACKENDLESS_USER_FIND` | Find User by ID | Tool to retrieve user information by ID. Use when you need to fetch details for a specific user after you have their objectId. | | `BACKENDLESS_USER_GRANT_PERMISSION` | Grant Permission to User | Tool to grant a permission to a user on a specific data object. Use when precise access rights must be assigned after verifying the table and object IDs. Example: "Grant FIND permission to a user for a Person record". | | `BACKENDLESS_USER_LOGIN` | User Login | Tool to log in a registered user with identity and password. Use when you need to authenticate a user before making subsequent requests. Example: "Login alice@wonderland.com with password wonderland". | | `BACKENDLESS_USER_LOGOUT` | User Logout | Tool to log out the currently authenticated user. Use when you need to terminate the user session after operations. | | `BACKENDLESS_USER_PASSWORD_RECOVERY` | User Password Recovery | Tool to initiate password recovery for a user. Use when a user requests a password reset after forgetting their password. Triggers an email with recovery instructions. | | `BACKENDLESS_USER_REGISTRATION` | User Registration | Tool to register a new user with email and password. Use when creating a user account or converting a guest account to a registered one after collecting credentials. Example: Register 'alice@wonderland.com' with password 'wonderland'. | | `BACKENDLESS_USER_REVOKE_PERMISSION` | Revoke Permission from User | Tool to revoke a permission from a specified user or role on a specific data object. Use when you need to deny a previously granted operation for a user or role on a data object after verifying the table and object IDs. | | `BACKENDLESS_USER_UPDATE` | Update User | Tool to update properties of an existing Backendless user. Use when you need to modify user profile fields after login. Example: Update phoneNumber to "5551212". | | `BACKENDLESS_VALIDATE_USER_TOKEN` | Validate User Token | Tool to validate a user session token. Use after obtaining a token from login to confirm the session is active. | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Backendless MCP server is an implementation of the Model Context Protocol that connects your AI agent to Backendless. It provides structured and secure access so your agent can perform Backendless operations on your behalf through a secure, permission-based interface. With Composio's managed implementation, you don't have to create your own developer app. For production, if you're building an end product, we recommend using your own credentials. The managed server helps you prototype fast and go from 0-1 faster. ## Step-by-step Guide ### 1. Prerequisites Before you begin, make sure you have: - Node.js and npm installed - A Composio account with API key - An OpenAI API key ### 1. Getting API Keys for OpenAI and Composio OpenAI API Key - Go to the [OpenAI dashboard](https://platform.openai.com/settings/organization/api-keys) and create an API key. You'll need credits to use the models, or you can connect to another model provider. - Keep the API key safe. Composio API Key - Log in to the [Composio dashboard](https://dashboard.composio.dev?utm_source=toolkits&utm_medium=framework_docs). - Navigate to your API settings and generate a new API key. - Store this key securely as you'll need it for authentication. ### 2. Install required dependencies First, install the necessary packages for your project. What you're installing: - @ai-sdk/openai: Vercel AI SDK's OpenAI provider - @ai-sdk/mcp: MCP client for Vercel AI SDK - @composio/core: Composio SDK for tool integration - ai: Core Vercel AI SDK - dotenv: Environment variable management ```bash npm install @ai-sdk/openai @ai-sdk/mcp @composio/core ai dotenv ``` ### 3. Set up environment variables Create a .env file in your project root. What's needed: - OPENAI_API_KEY: Your OpenAI API key for GPT model access - COMPOSIO_API_KEY: Your Composio API key for tool access - COMPOSIO_USER_ID: A unique identifier for the user session ```bash OPENAI_API_KEY=your_openai_api_key_here COMPOSIO_API_KEY=your_composio_api_key_here COMPOSIO_USER_ID=your_user_id_here ``` ### 4. Import required modules and validate environment What's happening: - We're importing all necessary libraries including Vercel AI SDK's OpenAI provider and Composio - The dotenv/config import automatically loads environment variables - The MCP client import enables connection to Composio's tool server ```typescript import "dotenv/config"; import { openai } from "@ai-sdk/openai"; import { Composio } from "@composio/core"; import * as readline from "readline"; import { streamText, type ModelMessage, stepCountIs } from "ai"; import { createMCPClient } from "@ai-sdk/mcp"; const composioAPIKey = process.env.COMPOSIO_API_KEY; const composioUserID = process.env.COMPOSIO_USER_ID; if (!process.env.OPENAI_API_KEY) throw new Error("OPENAI_API_KEY is not set"); if (!composioAPIKey) throw new Error("COMPOSIO_API_KEY is not set"); if (!composioUserID) throw new Error("COMPOSIO_USER_ID is not set"); const composio = new Composio({ apiKey: composioAPIKey, }); ``` ### 5. Create Tool Router session and initialize MCP client What's happening: - We're creating a Tool Router session that gives your agent access to Backendless tools - The create method takes the user ID and specifies which toolkits should be available - The returned mcp object contains the URL and authentication headers needed to connect to the MCP server - This session provides access to all Backendless-related tools through the MCP protocol ```typescript async function main() { // Create a tool router session for the user const session = await composio.create(composioUserID!, { toolkits: ["backendless"], }); const mcpUrl = session.mcp.url; ``` ### 6. Connect to MCP server and retrieve tools What's happening: - We're creating an MCP client that connects to our Composio Tool Router session via HTTP - The mcp.url provides the endpoint, and mcp.headers contains authentication credentials - The type: "http" is important - Composio requires HTTP transport - tools() retrieves all available Backendless tools that the agent can use ```typescript const mcpClient = await createMCPClient({ transport: { type: "http", url: mcpUrl, headers: session.mcp.headers, // Authentication headers for the Composio MCP server }, }); const tools = await mcpClient.tools(); ``` ### 7. Initialize conversation and CLI interface What's happening: - We initialize an empty messages array to maintain conversation history - A readline interface is created to accept user input from the command line - Instructions are displayed to guide the user on how to interact with the agent ```typescript let messages: ModelMessage[] = []; console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n"); console.log( "Ask any questions related to backendless, like summarize my last 5 emails, send an email, etc... :)))\n", ); const rl = readline.createInterface({ input: process.stdin, output: process.stdout, prompt: "> ", }); rl.prompt(); ``` ### 8. Handle user input and stream responses with real-time tool feedback What's happening: - We use streamText instead of generateText to stream responses in real-time - toolChoice: "auto" allows the model to decide when to use Backendless tools - stopWhen: stepCountIs(10) allows up to 10 steps for complex multi-tool operations - onStepFinish callback displays which tools are being used in real-time - We iterate through the text stream to create a typewriter effect as the agent responds - The complete response is added to conversation history to maintain context - Errors are caught and displayed with helpful retry suggestions ```typescript rl.on("line", async (userInput: string) => { const trimmedInput = userInput.trim(); if (["exit", "quit", "bye"].includes(trimmedInput.toLowerCase())) { console.log("\nGoodbye!"); rl.close(); process.exit(0); } if (!trimmedInput) { rl.prompt(); return; } messages.push({ role: "user", content: trimmedInput }); console.log("\nAgent is thinking...\n"); try { const stream = streamText({ model: openai("gpt-5"), messages, tools, toolChoice: "auto", stopWhen: stepCountIs(10), onStepFinish: (step) => { for (const toolCall of step.toolCalls) { console.log(`[Using tool: ${toolCall.toolName}]`); } if (step.toolCalls.length > 0) { console.log(""); // Add space after tool calls } }, }); for await (const chunk of stream.textStream) { process.stdout.write(chunk); } console.log("\n\n---\n"); // Get final result for message history const response = await stream.response; if (response?.messages?.length) { messages.push(...response.messages); } } catch (error) { console.error("\nAn error occurred while talking to the agent:"); console.error(error); console.log( "\nYou can try again or restart the app if it keeps happening.\n", ); } finally { rl.prompt(); } }); rl.on("close", async () => { await mcpClient.close(); console.log("\n๐Ÿ‘‹ Session ended."); process.exit(0); }); } main().catch((err) => { console.error("Fatal error:", err); process.exit(1); }); ``` ## Complete Code ```typescript import "dotenv/config"; import { openai } from "@ai-sdk/openai"; import { Composio } from "@composio/core"; import * as readline from "readline"; import { streamText, type ModelMessage, stepCountIs } from "ai"; import { createMCPClient } from "@ai-sdk/mcp"; const composioAPIKey = process.env.COMPOSIO_API_KEY; const composioUserID = process.env.COMPOSIO_USER_ID; if (!process.env.OPENAI_API_KEY) throw new Error("OPENAI_API_KEY is not set"); if (!composioAPIKey) throw new Error("COMPOSIO_API_KEY is not set"); if (!composioUserID) throw new Error("COMPOSIO_USER_ID is not set"); const composio = new Composio({ apiKey: composioAPIKey, }); async function main() { // Create a tool router session for the user const session = await composio.create(composioUserID!, { toolkits: ["backendless"], }); const mcpUrl = session.mcp.url; const mcpClient = await createMCPClient({ transport: { type: "http", url: mcpUrl, headers: session.mcp.headers, // Authentication headers for the Composio MCP server }, }); const tools = await mcpClient.tools(); let messages: ModelMessage[] = []; console.log("Chat started! Type 'exit' or 'quit' to end the conversation.\n"); console.log( "Ask any questions related to backendless, like summarize my last 5 emails, send an email, etc... :)))\n", ); const rl = readline.createInterface({ input: process.stdin, output: process.stdout, prompt: "> ", }); rl.prompt(); rl.on("line", async (userInput: string) => { const trimmedInput = userInput.trim(); if (["exit", "quit", "bye"].includes(trimmedInput.toLowerCase())) { console.log("\nGoodbye!"); rl.close(); process.exit(0); } if (!trimmedInput) { rl.prompt(); return; } messages.push({ role: "user", content: trimmedInput }); console.log("\nAgent is thinking...\n"); try { const stream = streamText({ model: openai("gpt-5"), messages, tools, toolChoice: "auto", stopWhen: stepCountIs(10), onStepFinish: (step) => { for (const toolCall of step.toolCalls) { console.log(`[Using tool: ${toolCall.toolName}]`); } if (step.toolCalls.length > 0) { console.log(""); // Add space after tool calls } }, }); for await (const chunk of stream.textStream) { process.stdout.write(chunk); } console.log("\n\n---\n"); // Get final result for message history const response = await stream.response; if (response?.messages?.length) { messages.push(...response.messages); } } catch (error) { console.error("\nAn error occurred while talking to the agent:"); console.error(error); console.log( "\nYou can try again or restart the app if it keeps happening.\n", ); } finally { rl.prompt(); } }); rl.on("close", async () => { await mcpClient.close(); console.log("\n๐Ÿ‘‹ Session ended."); process.exit(0); }); } main().catch((err) => { console.error("Fatal error:", err); process.exit(1); }); ``` ## Conclusion You've successfully built a Backendless agent using the Vercel AI SDK with streaming capabilities! This implementation provides a powerful foundation for building AI applications with natural language interfaces and real-time feedback. Key features of this implementation: - Real-time streaming responses for a better user experience with typewriter effect - Live tool execution feedback showing which tools are being used as the agent works - Dynamic tool loading through Composio's Tool Router with secure authentication - Multi-step tool execution with configurable step limits (up to 10 steps) - Comprehensive error handling for robust agent execution - Conversation history maintenance for context-aware responses You can extend this further by adding custom error handling, implementing specific business logic, or integrating additional Composio toolkits to create multi-app workflows. ## How to build Backendless MCP Agent with another framework - [OpenAI Agents SDK](https://composio.dev/toolkits/backendless/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/backendless/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/backendless/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/backendless/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/backendless/framework/codex) - [OpenClaw](https://composio.dev/toolkits/backendless/framework/openclaw) - [Hermes](https://composio.dev/toolkits/backendless/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/backendless/framework/cli) - [Google ADK](https://composio.dev/toolkits/backendless/framework/google-adk) - [LangChain](https://composio.dev/toolkits/backendless/framework/langchain) - [Mastra AI](https://composio.dev/toolkits/backendless/framework/mastra-ai) - [LlamaIndex](https://composio.dev/toolkits/backendless/framework/llama-index) - [CrewAI](https://composio.dev/toolkits/backendless/framework/crew-ai) ## Related Toolkits - [Supabase](https://composio.dev/toolkits/supabase) - Supabase is an open-source backend platform offering scalable Postgres databases, authentication, storage, and real-time APIs. It lets developers build modern apps without managing infrastructure. - [Codeinterpreter](https://composio.dev/toolkits/codeinterpreter) - Codeinterpreter is a Python-based coding environment with built-in data analysis and visualization. It lets you instantly run scripts, plot results, and prototype solutions inside supported platforms. - [GitHub](https://composio.dev/toolkits/github) - GitHub is a code hosting platform for version control and collaborative software development. It streamlines project management, code review, and team workflows in one place. - [Ably](https://composio.dev/toolkits/ably) - Ably is a real-time messaging platform for live chat and data sync in modern apps. It offers global scale and rock-solid reliability for seamless, instant experiences. - [Abuselpdb](https://composio.dev/toolkits/abuselpdb) - Abuselpdb is a central database for reporting and checking IPs linked to malicious online activity. Use it to quickly identify and report suspicious or abusive IP addresses. - [Alchemy](https://composio.dev/toolkits/alchemy) - Alchemy is a blockchain development platform offering APIs and tools for Ethereum apps. It simplifies building and scaling Web3 projects with robust infrastructure. - [Algolia](https://composio.dev/toolkits/algolia) - Algolia is a hosted search API that powers lightning-fast, relevant search experiences for web and mobile apps. It helps developers deliver instant, typo-tolerant, and scalable search without complex infrastructure. - [Anchor browser](https://composio.dev/toolkits/anchor_browser) - Anchor browser is a developer platform for AI-powered web automation. It transforms complex browser actions into easy API endpoints for streamlined web interaction. - [Apiflash](https://composio.dev/toolkits/apiflash) - Apiflash is a website screenshot API for programmatically capturing web pages. It delivers high-quality screenshots on demand for automation, monitoring, or reporting. - [Apiverve](https://composio.dev/toolkits/apiverve) - Apiverve delivers a suite of powerful APIs that simplify integration for developers. It's designed for reliability and scalability so you can build faster, smarter applications without the integration headache. - [Appcircle](https://composio.dev/toolkits/appcircle) - Appcircle is an enterprise-grade mobile CI/CD platform for building, testing, and publishing mobile apps. It streamlines mobile DevOps so teams ship faster and with more confidence. - [Appdrag](https://composio.dev/toolkits/appdrag) - Appdrag is a cloud platform for building websites, APIs, and databases with drag-and-drop tools and code editing. It accelerates development and iteration by combining hosting, database management, and low-code features in one place. - [Appveyor](https://composio.dev/toolkits/appveyor) - AppVeyor is a cloud-based continuous integration service for building, testing, and deploying applications. It helps developers automate and streamline their software delivery pipelines. - [Baserow](https://composio.dev/toolkits/baserow) - Baserow is an open-source no-code database platform for building collaborative data apps. It makes it easy for teams to organize data and automate workflows without writing code. - [Bench](https://composio.dev/toolkits/bench) - Bench is a benchmarking tool for automated performance measurement and analysis. It helps you quickly evaluate, compare, and track your systems or workflows. - [Better stack](https://composio.dev/toolkits/better_stack) - Better Stack is a monitoring, logging, and incident management solution for apps and services. It helps teams ensure application reliability and performance with real-time insights. - [Bitbucket](https://composio.dev/toolkits/bitbucket) - Bitbucket is a Git-based code hosting and collaboration platform for teams. It enables secure repository management and streamlined code reviews. - [Blazemeter](https://composio.dev/toolkits/blazemeter) - Blazemeter is a continuous testing platform for web and mobile app performance. It empowers teams to automate and analyze large-scale tests with ease. - [Blocknative](https://composio.dev/toolkits/blocknative) - Blocknative delivers real-time mempool monitoring and transaction management for public blockchains. Instantly track pending transactions and optimize blockchain interactions with live data. - [Bolt iot](https://composio.dev/toolkits/bolt_iot) - Bolt IoT is a platform for building and managing IoT projects with cloud-based device control and monitoring. It makes connecting sensors and actuators to the internet seamless for automation and data insights. ## Frequently Asked Questions ### What are the differences in Tool Router MCP and Backendless MCP? With a standalone Backendless MCP server, the agents and LLMs can only access a fixed set of Backendless tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Backendless and many other apps based on the task at hand, all through a single MCP endpoint. ### Can I use Tool Router MCP with Vercel AI SDK v6? Yes, you can. Vercel AI SDK v6 fully supports MCP integration. You get structured tool calling, message history handling, and model orchestration while Tool Router takes care of discovering and serving the right Backendless tools. ### Can I manage the permissions and scopes for Backendless while using Tool Router? Yes, absolutely. You can configure which Backendless scopes and actions are allowed when connecting your account to Composio. You can also bring your own OAuth credentials or API configuration so you keep full control over what the agent can do. ### How safe is my data with Composio Tool Router? All sensitive data such as tokens, keys, and configuration is fully encrypted at rest and in transit. Composio is SOC 2 Type 2 compliant and follows strict security practices so your Backendless data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) ยท [Composio docs](https://docs.composio.dev/llms.txt)